We are quickly passing through the historical moment when people work in front of a single computer, dominated by a small CRT and focused on tasks involving only local information. Networked computers are becoming ubiquitous and are playing increasingly significant roles in our lives and in the basic infrastructures of science, business, and social interaction. For human-computer interaction to advance in the new millennium we need to better understand the emerging dynamic of interaction in which the focus task is no longer confined to the desktop but reaches into a complex networked world of information and computer-mediated interactions. We think the theory of distributed cognition has a special role to play in understanding interactions between people and technologies, for its focus has always been on whole environments: what we really do in them and how we coordinate our activity in them. Distributed cognition provides a radical reorientation of how to think about designing and supporting human-computer interaction. As a theory it is specifically tailored to understanding interactions among people and technologies. In this article we propose distributed cognition as a new foundation for human-computer interaction, sketch an integrated research framework, and use selections from our earlier work to suggest how this framework can provide new opportunities in the design of digital work materials.

Code duplication is one of the factors that severely complicates the maintenance and evolution of large software systems. Techniques for detecting duplicated code exist but rely mostly on parsers, technology that has proven to be brittle in the face of different languages and dialects. In this paper we show that is possible to circumvent this hindrance by applying a language independent and visual approach, i.e. a tool that requires no parsing, yet is able to detect a significant amount of code duplication. We validate our approach on a number of case studies, involving four different implementation languages and ranging from 256 K up to 13Mb of source code size. Keywords: Software maintenance, code duplication detection, code visualization 1. Code Duplication Detection Duplicated code is a phenomenon that occurs frequently in large systems. The reasons why programmers duplicate code are manifold (see [9, 2] for a thorough discussion) and include the following reasons: (a) Making a ...

One of the most expensive and time-consuming components of the debugging process is locating the errors or faults. To locate faults, developers must identify statements involved in failures and select suspicious statements that might contain faults. This paper presents a new technique that uses visualization to assist with these tasks. The technique uses color to visually map the participation of each program statement in the outcome of the execution of the program with a test suite, consisting of both passed and failed test cases. Based on this visual mapping, a user can inspect the statements in the program, identify statements involved in failures, and locate potentially faulty statements. The paper also describes a prototype tool that implements our technique along with a set of empirical studies that use the tool for evaluation of the technique. The empirical studies show that, for the subject we studied, the technique can be effective in helping a user locate faults in a program.

Code-based metrics such as coupling and cohesion are used to measure a system’s structural complexity. But dealing with large systems—those consisting of several millions of lines — at the code level faces many problems. An alternative approach is to concentrate on the system’s building blocks such as programs or modules as the unit of examination. We present an approach that uses information in a release history of a system to uncover logical dependencies and change patterns among modules. We have developed the approach by working with 20 releases of a large Telecommunications Switching System. We use release information such as version numbers of programs, modules, and subsystems together with change reports to discover common change behavior (i.e. change patterns) of modules. Our approach identifies logical coupling among modules in such a way that potential structural shortcomings can be identified and further examined, pointing to restructuring or reengineering opportunities. 1

The data regarding the components of a software system consists of a large amount of information such as version history, number of lines, defect density, and complexity measures. The ability to quickly grasp a comprehensive view of the evolution and dependencies of such information is the key to making informed decisions about future developments of the system. Managers usually make such decision based only on expert judgement. For help in making such decisions, we can turn to the evolution history of large software systems, which contain a wealth of hidden information. Traditionally, this information is passed on through anecdotes without any supporting analytical data. This paper reports on our attempts to make such information more concrete through information visualization techniques. We present a threedimensional visual representation for examining a system’s software release history. The structure of the system is displayed by 2-D or 3-D graphs. The historical information is displayed by using time as the third dimension. Colors are used for displaying module properties and their historical changes in the system. A supporting software tool enables not only visualization but also navigation in the 3-D space to change the viewpoint, to browse system information, to find interesting patterns and to discover previously unknown relationships among system components.

We describe a system, called GPL, that implements a language for quantitative graphics. The structure of this system differs from existing statistical graphics, visualization, and mapping systems. Instead of treating a graphics display as a viewer for underlying data, GPL treats data as an accessory to viewing a graph. GPL is based on the mathematical definition of the graph of a function and uses that definition to organize data linked to the graph. To be published in Journal of Computational and Graphical Statistics. GPL has been renamed nViZn

Programmers frequently have to retrieve and link information from various software documents to accomplish a maintenance task. Ciao is a graph-based navigator that helps programmers query and browse structural connections embedded in different software and document repositories. A repository consists of a collection of source documents with an associated database that describes their structure. Ciao supports repositories organized in an architecture style called Aero, which exploits the duality between a class of entity-relationship (ER) databases and directed attributed graphs (DAG). Database queries and graph analysis operators in Aero are plug-compatible because they all take an ER database and produce yet another ER database by default. Various presentation filters generate graph views, source views, and relational views from any compatible ER database. The architecture promotes the construction of successively more complex operators using a notion of virtual database pipelines. Ci...

The SUIF Explorer is an interactive parallelization tool that is more effective than previous systems in minimizing the number of lines of code that require programmer assistance. First, the interprocedural analyses in the SUIF system is successful in parallelizing many coarse-grain loops, thus minimizing the number of spurious dependences requiring attention. Second, the system uses dynamic execution analyzers to identify those important loops that are likely to be parallelizable. Third, the SUIF Explorer is the first to apply program slicing to aid programmers in interactive parallelization. The system guides the programmer in the parallelization process using a set of sophisticated visualization techniques. This paper demonstrates the effectiveness of the SUIF Explorer with three case studies. The programmer was able to speed up all three programs by examining only a small fraction of the program and privatizing a few variables. 1. Introduction Exploiting coarse-grain parallelism i...

Software products are often released with missing functionality, errors, or incompatibilities that may result in failures in the field, inferior performances, or, more generally, user dissatisfaction. In previous work, we presented the Gamma technology, which facilitates remote analysis and measurement of deployed software and allows for gathering programexecution data from the field. When monitoring a high number of deployed instances of a software product, however, a large amount of data is collected. Such raw data are useless in the absence of a suitable data-mining and visualization technique that supports exploration and understanding of the data. In this paper, we present a new technique for collecting, storing, and visualizing program-execution data gathered from deployed instances of a software product. We also present a prototype toolset, Gammatella, that implements the technique. We show how the visualization capabilities of Gammatella allows for effectively investigating several kinds of execution-related information in an interactive fashion.

Corporate databases increasingly are being viewed as potentially rich sources of new and valuable knowledge. Various approaches to"discovering" or "mining " such knowledge have been proposed. Here we identify an important and previously ignored discovery task, which we call data archaeology. Data archaeology is a skilled human task, in which the knowledge sought depends on the goals of the analyst, cannot be specified in advance, and emerges only through an iterative process of data segmentation and analysis. We describe a system that supports the data archaeologist with a natural, objectoriented representation of an application domain, a powerful query language and database translation routines, and an easy-to-use and flexible user interface that supports interactive exploration. A formal knowledge representation system provides the core technology that facilitates database integration, querying, and the reuse of queries and query results. Keywords: data archaeology, knowledge discov...